An economy under the digital transformation

Bertani, Filippo and Ponta, Linda and Raberto, Marco and Teglio, Andrea and Cincotti, Silvano (2019): An economy under the digital transformation.

Abstract

During the last twenty years, we have witnessed the deep development of digital technologies. Artificial intelligence, software and algorithms have started to impact more and more frequently in our daily lives and most people didn't notice it. Recently, economists seem to have perceived that this new technological wave could have some consequences, but which one are they? Will they be positive or negative? In this paper we try to give a possible answer to these questions through an agent based computational approach; more specifically we enriched the large-scale macroeconomics model EURACE with the concept of digital technologies in order to investigate the effect that their business dynamics have at a macroeconomic level. Our preliminary results show that this productivity increase could be a double-edged sword: notwithstanding the development of the digital technologies sector can create new job opportunities, at the same time, these products could jeopardize the employment inside the traditional mass-production system.

• Item Type: MPRA Paper
• Language: English
• Keywords: Intangible assets, Industry 4.0, Digital revolution, Agent-based macroeconomics
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes

References

Acemoglu, D., Restrepo, P., 2017a. Low-Skill and High-Skill Automation. Working Paper 24119. National Bureau of Economic Research.

Acemoglu, D., Restrepo, P., 2017b. Robots and Jobs: Evidence from US Labor Markets. Working Paper 23285. National Bureau of Economic Research.

Acemoglu, D., Restrepo, P., 2018a. Artificial Intelligence, Automation and Work. Working Paper 24196. National Bureau of Economic Research.

Acemoglu, D., Restrepo, P., 2018b. Automation and new tasks: The implications of the task content of production for labor demand. Journal of Economic Perspectives.

Acemoglu, D., Restrepo, P., 2018c. Modeling Automation. Working Paper 24321. National Bureau of Economic Research.

Arthur, W.B., 1989. Competing technologies, increasing returns, and lock-in by historical events. Economic Journal 99, 116-31.

Arthur, W.B., 1990. Positive feedbacks in the economy. Scientific American.

Arthur, W.B., 1994. Increasing Returns and Path Dependence in the Economy. University of Michigan Press.

Arthur, W.B., 1999a. Complexity and the economy. Science 284, 107-109.

Arthur, W.B., 1999b. Increasing returns and the new world of business. Harvard business review 74.

Arthur, W.B., 2014. Complexity and the Economy. Oxford University Press.

Brynjolfsson, E., McAfee, A., 2011. Race Against The Machine: How The Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and The Economy. Digital Frontier Press.

Brynjolfsson, E., McAfee, A., 2014. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Co Inc.

Caiani, A., Russo, A., Gallegati, M., 2018. Does inequality hamper innovation and growth? an ab-sfc analysis. Journal of Evolutionary Economics.

Cotteleer, M.M., Sniderman, B., 2017. Forces of change: Industry 4.0. Deloitte Insights.

Dawid, H., Gemkow, S., Harting, P., Kabus, K., Wersching, K., Neugart, M., 2008. Skills, innovation, and growth: An agent-based policy analysis. Journal of Economics and Statistics 228, 251-275.

Dawid, H., Reimann, M., 2011. Diversification: a road to ineficiency in product innovations? Journal of Evolutionary Economics 21, 191-229.

Dosi, G., Fagiolo, G., Roventini, A., 2010. Schumpeter meeting keynes: A policy-friendly model of endogenous growth and business cycles. Journal of Economic Dynamics and Control 34, 1748-1767.

Elsner, W., Heinrich, T., Schwardt, H., 2014. The Microeconomics of Complex Economies. 1 ed., Elsevier.

Fanti, L., 2018. An AB-SFC Model of Induced Technical Change along Classical and Keynesian Lines. MPRA Paper. University Library of Munich, Germany.

Fontana, M., 2010. Can neoclassical economics handle complexity? the fallacy of the oil spot dynamic. Journal of Economic Behavior & Organization. 76, 584-596.

Gallegati, M., 2018. Complex agent-based models. New Economic Windows, Springer.

Godin, A., Caverzasi, E., 2014. Post-Keynesian stock- flow-consistent modelling: a survey. Cambridge Journal of Economics 39, 157-187.

Godley, W., Lavoie, M., 2016. Monetary economics: An integrated approach to credit, money, income, production and wealth. Palgrave Macmillan UK.

Haskel, J., Westlake, S., 2017. Capitalism without Capital. Princeton University Press.

Hommes, C., LeBaron, B., 2018. Computational Economics: Heterogeneous Agent Modeling. North Holland.

Kang, H.S., Lee, J.Y., Choi, S., Kim, H., Park, J.H., Son, J.Y., Kim, B.H., Noh, S.D., 2016. Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing-Green Technology 3, 111-128.

Kwoka, J., 1985. The Herfindahl index in theory and practice. Antitrust Bulletin 30, 915-947.

Mazzocchetti, A., Raberto, M., Teglio, A., Cincotti, S., 2018. Securitization and business cycle: an agent-based perspective. Industrial and Corporate Change 27, 1091-1121.

North, M., Macal, C., 2007. Managing Business Complexity: Discovering Strategic Solutions With Agent-Based Modeling and Simulation. Oxford University Press.

Ozel, B., Nathanael, R.C., Raberto, M., Teglio, A., Cincotti, S., 2019. Macroeconomic implications of mortgage loan requirements: an agent-based approach. Journal of Economic Interaction and Coordination.

Parrott, A., Lane, W., 2017. Industry 4.0 and the power of the digital twin. Deloitte University Press , 1-17.

Ponta, L., Raberto, M., Teglio, A., Cincotti, S., 2018. An Agent-based Stock-flow Consistent Model of the Sustainable Transition in the Energy Sector. Ecological Economics 145, 274-300.

Pyka, A., Gilbert, N., Ahrweiler, P., 2010. Agent-Based Modelling of Innovation Networks - The Fairytale of Spillover. volume 2009. pp. 101-126.

Raberto, M., Ozel, B., Ponta, L., Teglio, A., Cincotti, S., 2018. From financial instability to green finance: the role of banking and credit market regulation in the eurace model. Journal of Evolutionary Economics , 1-37.

Raberto, M., Teglio, A., Cincotti, S., 2012. Debt, deleveraging and business cycles: An agent-based perspective. Economics - The Open-Access, Open- Assessment E-Journal 6, 1-49.

Teglio, A., Mazzocchetti, A., Ponta, L., Raberto, M., Cincotti, S., 2017. Budgetary rigour with stimulus in lean times: Policy advices from an agent-based model. Journal of Economic Behavior & Organization.

Teglio, A., Raberto, M., Cincotti, S., 2012. The impact of banks' capital adequacy regulation on the economic system: An agent-based approach. Advances in Complex Systems 15.